neuronsimulator NEURON up to 9.0.2 bbcore_mech.dat stack-based overflow
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 4.9 | $0-$5k | 0.00+ |
Summary
A vulnerability has been found in neuronsimulator NEURON up to 9.0.2 and classified as problematic. Affected is an unknown function of the file bbcore_mech.dat. Performing a manipulation results in stack-based overflow. This vulnerability is known as CVE-2026-123203. Attacking locally is a requirement. No exploit is available.
Details
A vulnerability classified as problematic has been found in neuronsimulator NEURON up to 9.0.2. This affects an unknown part of the file bbcore_mech.dat. The manipulation with an unknown input leads to a stack-based overflow vulnerability. CWE is classifying the issue as CWE-121. A stack-based buffer overflow condition is a condition where the buffer being overwritten is allocated on the stack (i.e., is a local variable or, rarely, a parameter to a function). This is going to have an impact on integrity, and availability. The summary by CVE is:
NEURON (CoreNEURON) through 9.0.2 contains a stack buffer overflow vulnerability that allows attackers to corrupt stack memory by supplying over-long tokens in a crafted model dataset. Attackers can place oversized version or mechanism-name tokens in bbcore_mech.dat, globals.dat, or files.dat loaded by nrniv-core to crash the process.
It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-123203 since 11/05/2026. The exploitability is told to be easy. Attacking locally is a requirement. It demands that the victim is doing some kind of user interaction. Technical details of the vulnerability are known, but there is no available exploit.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 5.0VulDB Meta Temp Score: 4.9
VulDB Base Score: 3.9
VulDB Temp Score: 3.8
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 6.1
CNA Vector (VulnCheck): 🔒
CVSSv2
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Stack-based overflowCWE: CWE-121 / CWE-119
CAPEC: 🔒
ATT&CK: 🔒
Physical: Partially
Local: Yes
Remote: Partially
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
11/05/2026 Advisory disclosed11/05/2026 CVE reserved
11/05/2026 VulDB entry created
11/05/2026 VulDB entry last update
Sources
Advisory: github.comStatus: Not defined
CNA: VulnCheck
CVE: CVE-2026-123203 (🔒)
GCVE (CVE): GCVE-0-2026-123203
GCVE (VulDB): GCVE-100-431595
Entry
Created: 11/05/2026 19:40Changes: 11/05/2026 19:40 (74)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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